From Two Ladders to a Platform

The Orchestration Era started with a simple observation: engineering competency frameworks were built for a world where engineers write code. That world is ending. So we built two new ladders (one for ICs, one for people leaders) and published them for free. Then something interesting happened.

The Conversations We Didn't Expect

We expected engineering leaders to engage with the frameworks. They did. But the conversations that surprised us came from product leaders, design directors, and heads of data science, all saying some version of the same thing:

“This is exactly what's happening to my team too. Do you have anything for us?”

At first we thought these were adjacent problems with different solutions. But the more we listened, the more we realized: the abstraction line doesn't respect functional boundaries. It's rising everywhere that AI can absorb production work. And that's everywhere.

The Framework Explosion

So we built more. The AI-Native Product Management Ladder. The Product Design Ladder. The Data Science Ladder. An AI Leadership Ladder specifically for leaders driving AI adoption. A condensed 4-level IC Ladder for flatter organizations.

Each architecture follows the same methodology: take the traditional competency dimensions for a function, evaluate each one through the lens of “what happens when AI handles the production?”, and rebuild the framework around the competencies that remain uniquely human.

The dimensions are different for each function. A data scientist needs Statistical Reasoning & AI Foundations. A product designer needs Design Vision & AI Strategy. A product manager needs Discovery & Insight Generation. But the structural shift is identical: from producing artifacts to orchestrating outcomes.

From Frameworks to Platform

Publishing frameworks was the first step. But organizations don't just need to read about new competency standards. They need to operationalize them. That meant building tooling:

• •Org setup — Define your team structure and assign the right architecture to each person. An IC engineer and a product manager on the same team need different frameworks.
• •Guided assessment — Walk through each dimension with detailed expectations and real-world examples. Not just signals, but the full depth needed to make calibrated, defensible evaluations.
• •Growth plans — Once you know where someone stands, build a targeted development plan with clear next-level targets and a radar profile showing their competency shape.
• •Talent insights — See level distributions, competency heatmaps, and 9-box talent grids across teams and the entire org. Understand where your organization is strong and where the gaps are.

The Marketplace Bet

We also realized we couldn't build every architecture ourselves. Organizations have unique roles, hybrid functions, and domain-specific competency needs that no vendor can anticipate. So we built two things:

An architecture editor that lets you create entirely custom frameworks with your own levels, dimensions, and competency definitions, built from scratch or adapted from any built-in architecture.

And an architecture marketplace where the community can share what they've built. Browse frameworks created by other organizations, install them with one click, or publish your own for others to use.

The marketplace is our bet that the best competency frameworks will come from practitioners, not vendors. We provide the platform, the methodology, and the starting point. The community builds the long tail.

What Stays the Same

The thesis hasn't changed. The abstraction line is still rising. Roles are still shifting from production to orchestration. And organizations still need frameworks that measure the competencies that matter in this new world.

What changed is the scope. It's not just engineering. It's not just two ladders. It's a platform for evaluating and developing talent across every function that's being transformed by AI — which, increasingly, is all of them.